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Security Audit

phantom

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
35
CRITICAL
Scanned about 2 months ago
4
Critical
Immediate action required
1
High
Priority fixes suggested
0
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

phantom received a trust score of 35/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 5 findings: 4 critical, 1 high, 0 medium, and 0 low severity. Key findings include Network egress to untrusted endpoints, Unpinned dependency and arbitrary code execution from external URL in manifest, Arbitrary code execution from untrusted pastebin for macOS agent installation.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 0/100, indicating areas for improvement.

Last analyzed on February 14, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
70%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
0%

Behavioral Risk Signals

Network Access
4 findings
Shell Execution
4 findings
Dynamic Code
2 findings
Excessive Permissions
1 finding

Security Findings5

SeverityFindingLayerLocation

Scan History

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